Add references with sphinxcontrib-bibtex

docs/source/conf.py

@@ -47,12 +47,17 @@
     "sphinx.ext.autosectionlabel",
     "sphinx_autodoc_typehints",
     "sphinx_toolbox.more_autodoc.autoprotocol",
+    "sphinxcontrib.bibtex",
 ]
 
 nbsphinx_allow_errors = True  # optional, avoids build breaking due to execution errors
 
 templates_path = ["_templates"]
 exclude_patterns = ["_build", "Thumbs.db", ".DS_Store"]
+bibtex_bibfiles = ["references.bib"]
+bibtex_default_style = (
+    "alpha"  # set to alpha to not confuse references the docs with the footcites in docstrings.
+)
 
 source_suffix = {
     ".rst": "restructuredtext",

docs/source/example.md

@@ -0,0 +1,3 @@
+# Example
+`shapiq` is a Library for computing Shapley Interactions and Shapley Values
+for Machine Learning {cite:p}`muschalikShapleyInteractions2024`.

docs/source/index.rst

@@ -59,4 +59,5 @@ Contents
    :maxdepth: 1
    :caption: BIBLIOGRAPHY
 
-   references
+   example
+   references_alternative

docs/source/references.bib

@@ -0,0 +1,24 @@
+@inproceedings{muschalikShapleyInteractions2024,
+  author       = {Maximilian Muschalik and
+                  Hubert Baniecki and
+                  Fabian Fumagalli and
+                  Patrick Kolpaczki and
+                  Barbara Hammer and
+                  Eyke H{\"{u}}llermeier},
+  editor       = {Amir Globersons and
+                  Lester Mackey and
+                  Danielle Belgrave and
+                  Angela Fan and
+                  Ulrich Paquet and
+                  Jakub M. Tomczak and
+                  Cheng Zhang},
+  title        = {shapiq: Shapley Interactions for Machine Learning},
+  booktitle    = {Advances in Neural Information Processing Systems 38: Annual Conference
+                  on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver,
+                  BC, Canada, December 10 - 15, 2024},
+  year         = {2024},
+  url          = {http://papers.nips.cc/paper\_files/paper/2024/hash/eb3a9313405e2d4175a5a3cfcd49999b-Abstract-Datasets\_and\_Benchmarks\_Track.html},
+  timestamp    = {Thu, 13 Feb 2025 16:56:45 +0100},
+  biburl       = {https://dblp.org/rec/conf/nips/MuschalikBFKHH24.bib},
+  bibsource    = {dblp computer science bibliography, https://dblp.org}
+}

docs/source/references_alternative.rst

@@ -0,0 +1,5 @@
+📚 Bibliography
+===============
+
+.. bibliography::
+   :cited:

pyproject.toml

@@ -231,6 +231,7 @@ docs = [
     "sphinx-copybutton",
     "sphinx-autodoc-typehints",
     "sphinx_toolbox",
+    "sphinxcontrib-bibtex", # references based on bibtex
     "nbconvert",
     "nbsphinx",
     "commonmark",  # Markdown parser and renderer

shapiq/plot/si_graph.py

@@ -61,7 +61,7 @@ def si_graph_plot(
     represent interactions between the players. The size of the nodes and edges represent the
     strength of the interaction values. The color of the edges represents the sign of the
     interaction values (red for positive and blue for negative). The SI-graph plot is presented in
-    Muschalik et al. (2024)[1]_.
+    :footcite:t:`muschalikShapleyInteractions2024`.
 
     Args:
         interaction_values: The interaction values to plot.
@@ -146,7 +146,7 @@ def si_graph_plot(
         The figure and axis of the plot if ``show`` is ``False``. Otherwise, ``None``.
 
     References:
-        .. [1] Muschalik, M., Baniecki, H., Fumagalli, F., Kolpaczki, P., Hammer, B., and Hüllermeier, E. (2024). shapiq: Shapley Interactions for Machine Learning. In: The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track. url: https://openreview.net/forum?id=knxGmi6SJi#discussion.
+        .. footbibliography::
     """
     if interaction_values is None:
         msg = "Interaction_values must be provided."